Case Studies

Newsfeed Optimization: Driving Facebook Reach and Website Traffic

GOOD Inc. is an online news outlet and community working towards a better world. When we first started working with them, they had over 100,000 fans on Facebook with fantastic original, user-generated content.

The two main goals:

Maximize reach and visibility on Facebook.

Drive traffic to their website to generate more revenue.

THE PROBLEMS

#1: Facebook users never come back to a fan page after liking it for the first time. The below graph is from a fan page that has over 3 million fans. Notice that the average number of people coming back to the fan page on a given day is around 2,000, extremely low in comparison to the size of the page. GOOD Inc. had to reach their fans through the news feed.

#2: The second part of the problem only complicates the first part: Saturation. GOOD Inc. was trying to grow their reach and visibility at the very same time that Facebook was growing exponentially. More and more user accounts and brand pages were being added every day. This led to an extremely full news feed, with thousands of pieces of content fighting to get seen by users.

HOW FACEBOOK WORKS

The average page on Facebook only reaches 7-12% of their audience, with that percentage slowly declining as Facebook gets more cluttered. EdgeRank is the algorithm that Facebook initially created to decide which pieces of content make it into a user’s news feed.

The 3 parts of EdgeRank:

EdgeScore: This is a hard value score determined by the kind of content you post in a status update, such as a photo, video, or link.

Affinity sore: This is the relationship between the user and the fan page. The stronger the relationship, the higher the affinity score. The higher the affinity score, the more likely the user is to see a content from the fan page.

Time Decay: This is defined by what time of day you post. It also determines how long a status update will last in the news feed.

THE SOLUTION

For GOOD Inc., we aggressively tested the three variables of EdgeRank to find the optimal strategy to reach our goals. This included testing different types of updates, the copy that was used, the questions that were asked and the length of the copy. We tested different types of photos and graphics. We broke down the audience by geographical location and used this to optimize the timing of the posts.